A model for simulating schedule risks in prefabrication housing production: A case study of six-day cycle assembly activities in Hong Kong. (1st June 2018)

• Record Type: Journal Article
• Authors: Li, Clyde Zhengdao; Xu, Xiaoxiao; Shen, Geoffrey Qiping; Fan, Cheng; Li, Xiao; Hong, Jingke
• Is Part Of: Journal of cleaner production. Volume 185(2018)
• Page Start: 366
• Page End: 381
• Publication Date: 2018-06-01
• Subjects: Prefabrication housing production -- Schedule risks -- System dynamics -- Discrete event simulation -- Six-day cycle assembly; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.02.308
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The construction industry in Hong Kong has been exposed to serious housing production issues such as insufficient manpower, safety, environmental concerns and inefficient housing supply. Prefabrication housing production has shown as efficient construction model which enables to overcome these issues and it is applied in construction industry in Hong Kong. In this paper, hybrid modeling techniques that combine system dynamics and discrete event simulation are used to analyze the interrelationships of schedule risks within the six-day cycle assembly of prefabrication housing production. Moreover, a hybrid dynamic model is developed to simulate and evaluate the impact of schedule risks on the schedule performance of the six-day cycle assembly of PHP via the Anylogic software package. The resulting model is validated by data which is collected from a PHP project in Hong Kong. Based on the simulation results, the first most influential level contains five schedule risks, namely, inefficient verification of precast components because of ambiguous labels, misplacement on the storage site because of carelessness, owner crane breakdown and maintenance, slow quality inspection procedures, and inefficient design data transition that cause average schedule delays of more than 300 min. The second most influential level includes delay of the delivery of precast element to site, design information gap between designer and manufacturer, installation error of precast elements, and logistics information inconsistency because of human errors, with average schedule delays less than 300 min and greater than 200 min. Design change, low information interoperability between different enterprise resource planning systems, and inefficiency of design approval belong to the third level that imposes the least influence on the schedule delay of the assembly. This research contributes to the current knowledge of the management of prefabrication construction by developing an effective model that offers an in-depth understanding of how schedule performance of PHP is dynamically influenced by interrelationships of various risk variables. Also, it provides an experimental platform for simulating and analyzing schedule risks that significantly affect the schedule performance of the six-day cycle assembly of prefabrication housing production. Such critical schedule risks could be identified and managed prior to the implement of prefabrication housing production projects. Compared with traditional techniques, the hybrid dynamic model simultaneously considers macro and micro levels, thereby enabling project managers to gain a deeper insight into schedule management and acquire a multidimensional understanding of schedule delay.